Search Results - (( simulation optimization methods algorithm ) OR ( feature selection method algorithm ))

Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…Next, four recently introduced optimization algorithms are employed as feature selector, namely as 1) angle modulated simulated Kalman filter (AMSKF), 2) binary simulated Kalman filter (BSKF), 3) local optimum distance evaluated simulated Kalman filter (LocalDESKF), and 4) global optimum distance evaluated simulated Kalman filter (GlobalDESKF). …”
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HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION by GHADA HAMMAD AL-RAWASHDEH

“…The proposed method is based on the hybridization of Water Cycle Algorithm with the Simulated Annealing to optimize the results. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

“…In this paper, a hybrid electricity price forecasting method which is composed of two-stage feature selection method and optimized adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine is proposed to accurately forecast electricity price. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

“…In these extended IFS method, feature selection method was defined and presented as a 0-1 Knapsack Problem (MKP). …”
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Optimal selection of long time acoustic features using GA for the assessment of vocal fold disorders by Sindhu, Ravindran, Neoh, Siew Chin, Dr., Muthusamy, Hariharan, Dr.

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Robust correlation feature selection based support vector machine approach for high dimensional datasets by Baba, Ishaq Abdullahi, Mohammed, Mohammed Bappah, Jillahi, Kamal Bakari, Umar, Aliyu, Hendi, Hasan Talib

“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Actual data sets are collected from Ontario electricity market of the year 2017 for the verification of simulation results. Finally, the simulation results validated the premise of the proposed hybrid method through enhanced accuracy compared to the results acquired by implementing hybrid support vector machine (SVM) and hybrid ANN optimization methods. © 2013 IEEE.…”
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Feature Selection using Angle Modulated Simulated Kalman Filter for Peak Classification of EEG Signals by Asrul, Adam, Zuwairie, Ibrahim, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Marizan, Mubin, Ismail, Saad

“…A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Cuckoo search), and evaluator or model inducing algorithms (e.g SVM) were utilized for feature subset selection, which further compared to select the optimal conditioning factors subset. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…The dataset development for both algorithms is carried out via simulations in Graphical Network Simulator 3 (GNS3). …”

Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony by Mohd Izuddin Sipluk

“…During the methodology chapter, a comprehensive investigation has been done to ascertain the proposed method that can be adopted such as algorithms involved, project flow, and simulation. …”
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Feature selection using angle modulated simulated Kalman filter for peak classification of EEG signals by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M., Saad, I.

“…A new optimization algorithm, namely as angle modulated simulated Kalman filter (AMSKF) will be employed as feature selector. …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…However, determining the essential behavioral outputs for autonomous driving vehicle systems or selecting the optimal output features to learn from them is not easy. …”
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

“…In this thesis, new non-linear feature-selection assisted methods and ensemble learning models are proposed. …”
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Enhancing land cover classification in remote sensing imagery using an optimal deep learning model by Motwake, Abdelwahed, Hassan Abdalla Hashim, Aisha, Obayya, Marwa, Eltahir, Majdy M.

“…Since ‘manual hyperparameter tuning’ is an erroneous and laborious task, the AIMS Mathematics Volume 9, Issue 1, 140–159. hyperparameter selection is accomplished with the help of the Reptile Search Algorithm (RSA). …”
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Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

“…To fill-in the gap in the literature, a new robust procedure in wavelength selection based on input scaling method is developed using Filter-Wrapper method. …”
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